What can we learn from - PowerPoint Presentation

Slide1

What can we learn from Vital Statistics about the determinants of weekend births and male births?

Prepared for Presentation at the

Offord

Centre for Child Studies

4 February 2015

Byron G SpencerSlide2

Many Data Sets in the RDCE.g., Vital Statistics –

an administrative database

Live births; deaths

Close to universal coverage

Application of the Birth file

I’ll focus on the management and analysis of this large file (≈375K/

yr

)

An early concern was to check for missing data and other problems

E.g., the files go back to 1974, but some variables not well reported, especially in the early years

‘Place of birth’ missing for 25% of births before 1990Slide3

Vital Statistics – Births Information is limited:

Event itself:

When (to the day)

Where (name of

city/town/village, census subdivision)

Place (hospital, home, other)

Number of children in this event

Number stillborn

For each

live born

child –

Sex

Birth order

Duration of pregnancy

Weight

Attendant (MD, RN, midwife, other, unknown)Slide4

…file content (cont’d)Mother’s

Age

Birthplace (province; country)

Usual residence (postal code)

Marital status (single, married, divorced, separated)

Number of children ever

live born

Number of children ever stillborn

Father’s

Age

Birthplace

(province; country)

Parent’s

Marital relationship (married to each other?)Slide5

Weekend births If nature had its way, one-sevenths of births, 14.3 percent, would occur on each day of the

weekSlide6

… but that is not what happensSlide7

What can we learn from the VS records?

WB = f(DUR, WT, SEX, MULT, AGE, PARITY, STILL, IMM, HOSP, PROV, MONTH, YEAR)

where

: WB –

=

1 if birth occurred on the weekend; 0 if on weekday

DUR –

duration

of pregnancy (5 categories)

WT

– birth

weight (x categories)

SEX –

=

1 if child is male; 0 if female

MULT –

=

1 if more than one birth at this event; 0 if not

AGE –

age

of mother (7 categories)

PARITY –

birth

parity (4 categories)

STILL –

=

1 if previous stillbirth; 0 otherwise

IMM –

=

1 if mother born outside Canada; 0

otherwise

HOSP –

=

1 if not born in hospital; 0 otherwise

PROV –

place

(usually province) of birth (13 categories)

MONTH –

month

of birth (12 categories)

YEAR –

year

of birth (10 categories)Slide8

More likely to happen on weekends – Single births –

almost

5

percentage points

more likely than multiple births

Early births

--

6.5

percentage points

more likely if

<35

wks

rather than

40

+

Younger mothers

–

3.7

percentage points

more likely if under

20

rather than 45

or older

No prior still birth –

1.2

percentage points more likely

First births –

3

percentage points

more likely than

s

econd or higher order births

Births outside of hospitals (a very small proportion of the total)

About

4 percentage points more

likely, or

about equally likely to occur on any day of the week

Immigrant

women –

1.1

percentage points more likelySlide9

What about the probability of a male birth?Slide10
Slide11
Slide12

… with Canadian birth data we askIs there evidence of sex-selection?

Specifically among immigrants?Slide13

Equation estimated -- M = f(AGE, STILL,

PARENTCoB

, PROV, YEAR)

where: M –

=

1 if male birth; 0 if female

AGEmother

–

age

of mother (7 categories)

AGEfather

–

age

of father (7 categories)

STILL –

=

1 if previous stillbirth; 0 otherwise

PARENTCoB

–

=

1 if both parents born in country j; 0 otherwise

PROV –

place

(usually province) of birth (13 categories)

YEAR –

year

of birth (10 categories)Slide14

VariantsThe equation is estimated with the observations restricted as follows

First or later birth

Second or later birth

Third or later birth

Fourth or later birthSlide15

Here is a summary of the resultsSlide16

Male/Female Birth Proportions by Birthplace of Parents and Number of Births